Observation Instance – Django REST framework

Get a list of Observation objects.

### Available end points:

- `/observations/` - Will list all Results in the database
- `/observations.json` - Will return all Results in json format. This can
also be achieved by using the accept header. `application/json`
- `/observations/<object_id>/` - Returns Results object with that id

### Available Methods:

- `GET`
- `HEAD`

### Available filters:

- `title`
- `uuid`
- `keywords`
- `status`
- `result_field`
- `discoveryKeywords`
- `updateFrequency`
- `nonGeographicFlag`
- `publicationState`
- `permissions`

### How to use filters:

These filters can be used like django query filters using __ for related model relationships.

- `/observations/?uuid=d594d53df2612bbd89c2e0e770b5c1a0`
- `/observations/?status=completed`
- `/observations/?results_field__dataPath__startswith=/neodc/esacci`
- `/observations/?discoveryKeywords__name=ESACCI`
- `/observations/?nonGeographicFlag=True`

Filters can be stacked to build an 'AND' relationship. E.g.

- `/observations/?publicationState__in=published,citable&nonGeographicFlag=True`
- `/observations/?publicationState__in=published,citable&discoveryKeyword__name=NDGO0003`

GET /api/v2/observations/40853/?format=api

HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "ob_id": 40853,
    "uuid": "7bef89a9dc404683a46642625a024a4b",
    "title": "ForestScan: Aerial Laser Scanning (ALS) of FBRMS-01: Paracou, French Guiana, November 2022",
    "abstract": "This Aerial Laser Scanning (ALS) campaign was conducted in November 2022. The ALS data corresponding to plots FG5c1, FG6c2, FG8c4 and IRD-CNES also scanned by Terrestrial LiDAR Scanning (TLS) in October or November 2022 as part of the ForestScan Project are provided in four separate laz files.\r\n\r\nThe covered area: 3*2.16 ha + 1*1.44 ha; Pulse density: ~200 m2; Scanner type: VQ 780II RIEGL; Scanner wavelength: 1064 nm; Beam divergence: <=0.25 mrad (1/e2); Vehicle: Airplane BN2; Operator: Altoa. Acquisition parameters: swath angle: +/-20 degrees; PRR (channel type): ~ 1000 kHz; Ground footprint size of pulse: ~0.16 m;  Flight height: 650m  terrain follow mode (AGL); Acquisition mode: Full waveform, RGB camera on board but no orthomosaïc made.",
    "keywords": "ForestScan project, GEO-TREES, BIOMASS mission, European Space Agency (ESA), Earth Observation (EO) calibration/validation, Unpiloted Aerial Vehicle LiDAR Scanning (UAV-LS), Aerial LiDAR Scanning (ALS), Digital twins, Forest structure",
    "publicationState": "citable",
    "dataPublishedTime": "2025-03-28T14:45:28",
    "doiPublishedTime": "2025-03-28T16:52:41.441488",
    "updateFrequency": "",
    "status": "completed",
    "result_field": {
        "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/43413/?format=api",
        "dataPath": "/neodc/forestscan/data/french_guiana/paracou/ALS-Paracou-2022-PerPlot",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 168157094,
        "numberOfFiles": 6,
        "fileFormat": "Storage format is las 1.2 (terrestrial laser scanner)"
    },
    "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/12163/?format=api",
    "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/3953/?format=api",
    "nonGeographicFlag": false,
    "phenomena": [],
    "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA) by Gregoire Vincent.",
    "removedDataTime": null,
    "removedDataReason": "",
    "language": "English",
    "identifier_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/13273/?format=api"
    ],
    "projects": [
        "https://api.catalogue.ceda.ac.uk/api/v2/projects/40337/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/projects/43702/?format=api"
    ],
    "observationcollection_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/40623/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/30128/?format=api"
    ],
    "responsiblepartyinfo_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198708/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198709/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198710/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198711/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198712/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198713/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/209142/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/209143/?format=api"
    ],
    "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/43710/?format=api",
    "procedureCompositeProcess": null,
    "procedureComputation": null,
    "permissions": [
        {
            "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2528/?format=api",
            "useLimitation": null,
            "accessConstraints": null,
            "accessCategory": "public",
            "accessRoles": null,
            "label": "public: None group",
            "licenceURL": "http://creativecommons.org/licenses/by/4.0/",
            "licenceClassifications": "any"
        }
    ],
    "discoveryKeywords": [
        {
            "ob_id": 1138,
            "name": "NDGO0003"
        }
    ]
}